Linear Algebra and Optimization with Applications to Machine Learning
Overview & Synopsis
This book applies the linear algebra concepts to optimization problems which frequently occur throughout machine learning. Highlights include careful derivations and applications of the simplex algorithm, the dual-simplex algorithm, and the primal-dual algorithm.
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Document Information
| Document Title | Linear Algebra and Optimization with Applications to Machine Learning |
|---|---|
| Author / Organization | Jean Gallier and Jocelyn Quaintance |
| Subject & Discipline | Linear Algebra, Matrix Algebra, and Linear Systems, Machine Learning, Optimization Problems |
| Categories | Linear Algebra, Matrix Algebra, and Linear Systems |
| Publication Year | 2020 |
| ISBN | 978-9811216565 |
| Resource Verification | ✓ Verified Direct PDF Available |
| Original Host Website |
FreeComputerBooks.com
(freecomputerbooks.com)
|
| File Format | application/pdf (Portable Document Format) |
| Reported File Size | 9738.8 KB (9,972,563 bytes) |
| Language | ENGLISH |
| Catalog ID | DOC-9721 |
| Original Source Link | Visit Source Page on freecomputerbooks.com » |
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